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author | Travis Oliphant <oliphant@enthought.com> | 2008-03-07 21:32:04 +0000 |
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committer | Travis Oliphant <oliphant@enthought.com> | 2008-03-07 21:32:04 +0000 |
commit | 62e994938e1549b28117684efcff58d6c6adbc77 (patch) | |
tree | 00d1dd47dea5c0e431401ffaa14738cc59fd2b7e /numpy/core/fromnumeric.py | |
parent | 0ef3f8b15dd80e95f1d85298bab7954d61419ac4 (diff) | |
download | numpy-62e994938e1549b28117684efcff58d6c6adbc77.tar.gz |
Add ddof parameter to std and var computations.
Diffstat (limited to 'numpy/core/fromnumeric.py')
-rw-r--r-- | numpy/core/fromnumeric.py | 22 |
1 files changed, 14 insertions, 8 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index 66f54ccb1..23e2a3229 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -1631,7 +1631,7 @@ def mean(a, axis=None, dtype=None, out=None): return mean(axis, dtype, out) -def std(a, axis=None, dtype=None, out=None): +def std(a, axis=None, dtype=None, out=None, ddof=0): """Compute the standard deviation along the specified axis. Returns the standard deviation of the array elements, a measure of the @@ -1654,6 +1654,9 @@ def std(a, axis=None, dtype=None, out=None): Alternative output array in which to place the result. It must have the same shape as the expected output but the type will be cast if necessary. + ddof : {0, integer} + Means Delta Degrees of Freedom. The divisor used in calculations + is N-ddof. Returns ------- @@ -1670,8 +1673,8 @@ def std(a, axis=None, dtype=None, out=None): ----- The standard deviation is the square root of the average of the squared deviations from the mean, i.e. var = sqrt(mean((x - x.mean())**2)). The - computed standard deviation is biased, i.e., the mean is computed by - dividing by the number of elements, N, rather than by N-1. + computed standard deviation is computed by dividing by the number of + elements, N-ddof. Examples -------- @@ -1687,11 +1690,11 @@ def std(a, axis=None, dtype=None, out=None): try: std = a.std except AttributeError: - return _wrapit(a, 'std', axis, dtype, out) - return std(axis, dtype, out) + return _wrapit(a, 'std', axis, dtype, out, ddof) + return std(axis, dtype, out, ddof) -def var(a, axis=None, dtype=None, out=None): +def var(a, axis=None, dtype=None, out=None, ddof=0): """Compute the variance along the specified axis. Returns the variance of the array elements, a measure of the spread of a @@ -1714,6 +1717,9 @@ def var(a, axis=None, dtype=None, out=None): Alternative output array in which to place the result. It must have the same shape as the expected output but the type will be cast if necessary. + ddof : {0, integer}, + Means Delta Degrees of Freedom. The divisor used in calculation is + N - ddof. Returns ------- @@ -1747,5 +1753,5 @@ def var(a, axis=None, dtype=None, out=None): try: var = a.var except AttributeError: - return _wrapit(a, 'var', axis, dtype, out) - return var(axis, dtype, out) + return _wrapit(a, 'var', axis, dtype, out, ddof) + return var(axis, dtype, out, ddof) |